Multiple approaches to developing driverless vehicles and automating conventional vehicles (e.g., manually-driven automotive vehicles) are principally directed to autonomous driving based on sensor data, such as image data, location data, radar, etc. These autonomous driving approaches generally focus on navigating a vehicle from a first location to a second location with little to no human involvement. In some approaches, semi-autonomous and fully-autonomous vehicles require a human driver to identify signs, symbols, and the like to determine a location to park an autonomous vehicle while complying with all laws, restrictions, or privileges associated with the parking location.
Certain approaches to parking an autonomous vehicle may include analyzing a parking space with onboard sensors to determine parking space size, allowing an autonomous system to physically maneuver an autonomous vehicle into the parking space. However, contemporary systems do not address the issue of restrictions and permissions associated with the parking space. This is more problematic in dense cities where multiple parking permissions and restrictions may apply to a single parking space.
Thus, what is needed is a solution for identifying, with little to no human involvement, permissioned parking relative to multiple classes of restricted and privileged parking.